Phase II of the Copernicus Marine In Situ Thematic Assembly Center was officially launched with a kick-off meeting from March 4-6, 2025 at the Puertos del Estado headquarters in Madrid. This phase is an important step towards improving the accessibility, quality and integration of oceanographic in-situ data within the Copernicus Marine Service.
The main activities and developments planned for this phase are summarized below.
Development of partners: The University of La Rochelle has joined as a new partner, while Now Systems replaces SOCIB in the marineinsitu website team.
Improvements to Near Real Time (NRT) in situ data products: The project is introducing a consolidated approach to multi-year NRT products by moving from seven regional products to a single global MYNRT product with multiple parameters. This transition will ensure continued regional expertise and direct collaboration between partners and providers. In addition, the project will introduce ice parameters for the Arctic (ARC), Baltic (BAL) and Black Sea (BLK), which includes identifying data sources, creating metadata and vocabulary, implementing NRT quality control and setting up data flow.
Improvements to the multi-year (MY) products include: Expansion of the UV product to include new data sources such as ADCPs and gliders, improved drifter dataset with more robust data processing, uncertainty analysis, quality control and drogue loss information, and hourly sea surface temperature (SST) data. Moreover, the sea level product will integrate more data outside Europe from the GLOSS networks, will extend existing tide and surge dataset to other European regions and will add a GNSS correction of land vertical motion. In addition, the wave product will be improved by integrating tide gauge data and HF radar data (at pilot sites). Accordingly, the BGC and carbon products will be merged to ensure that the carbon datasets are consistent with other in situ data, to optimize quality control and data flow, and more user-friendly BGC datasets will be added for each parameter of this upgraded BGC product.
Quality control procedures will be improved by applying MinMax methods to oxygen data, refining spatial-regional range tests, and comparing near-real-time (NRT) and delayed-mode (DM) method versions. In addition, artificial intelligence (AI) techniques for quality control will be integrated, with CTD data processing already in operation and a prototype for HF radar data being developed.
